/*
 * Copyright (c) 2023-2025 elsfs Authors. All Rights Reserved.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.elsfs.cloud.module.ai.biz.controller;

import dev.langchain4j.data.document.Document;
import dev.langchain4j.data.document.loader.FileSystemDocumentLoader;
import dev.langchain4j.data.document.parser.apache.tika.ApacheTikaDocumentParser;
import dev.langchain4j.data.document.splitter.DocumentByLineSplitter;
import dev.langchain4j.memory.chat.MessageWindowChatMemory;
import dev.langchain4j.model.openai.OpenAiChatModel;
import dev.langchain4j.rag.content.retriever.EmbeddingStoreContentRetriever;
import dev.langchain4j.service.AiServices;
import dev.langchain4j.store.embedding.EmbeddingStoreIngestor;
import java.util.List;
import lombok.RequiredArgsConstructor;
import lombok.extern.slf4j.Slf4j;
import org.elsfs.cloud.common.annotations.security.IgnoringAuthentication;
import org.elsfs.cloud.module.ai.api.service.AiEmbeddingStoreService;
import org.elsfs.cloud.module.ai.biz.service.Assistant;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;

/**
 * ai 聊天
 *
 * @author zeng
 */
@Slf4j
@RequestMapping("/ai")
@RequiredArgsConstructor
@RestController
public class AiChatController {

  private final AiEmbeddingStoreService aiEmbeddingStoreService;

  /**
   * 聊天
   *
   * @param userMessage 聊天
   * @return 聊天
   */
  @GetMapping("/chat")
  @IgnoringAuthentication
  public String chat(
      @RequestParam(value = "msg", defaultValue = "怎么新建一个模块，模块是order，名称是订单") String userMessage) {

    List<Document> documents =
        FileSystemDocumentLoader.loadDocuments(
            getClass().getClassLoader().getResource("rag").getPath(),
            new ApacheTikaDocumentParser());
    var embeddingStore = aiEmbeddingStoreService.getEmbeddingStoreByStoreId("1935344286862430209");
    // 默认我们选择bge-small-en-v1.5作为 Easy RAG 的默认嵌入模型
    EmbeddingStoreIngestor.builder()
        // LangChain4j 具有DocumentSplitter多个开箱即用的实现接口：
        // DocumentByParagraphSplitter  按段落拆分文档
        .documentSplitter(new DocumentByLineSplitter(48, 20))
        .embeddingStore(embeddingStore)
        .build()
        .ingest(documents);
    OpenAiChatModel chatModel =
        OpenAiChatModel.builder()
            .modelName("deepseek-chat")
            .apiKey(System.getenv("DEEPSEEK_KEY"))
            .baseUrl("https://api.deepseek.com")
            .build();
    Assistant assistant =
        AiServices.builder(Assistant.class)
            .chatModel(chatModel)
            .systemMessageProvider(chatMemoryId -> "你是一名专业程序员，回答的时候需要更精确") // 系统提示词
            .chatMemory(MessageWindowChatMemory.withMaxMessages(10))
            .contentRetriever(EmbeddingStoreContentRetriever.from(embeddingStore))
            .build();
    return assistant.chat(userMessage);
  }

  //  /**
  //   * 流式返回
  //   *
  //   * @param request request
  //   * @param response response
  //   * @return s
  //   */
  //  @PostMapping(
  //      value = "/stream",
  //      produces = MediaType.TEXT_EVENT_STREAM_VALUE,
  //      consumes = MediaType.APPLICATION_JSON_VALUE)
  //  public Flux<String> streamChat(
  //      @RequestBody StreamChatRequest request, HttpServletResponse response) {
  //
  //    response.setCharacterEncoding("UTF-8");
  //
  //    UserMessage userMessage = UserMessage.from(request.message());
  //
  //    List<ChatMessage> messages = List.of(userMessage);
  //
  //    OllamaStreamingChatModel chatModel =
  //        OllamaStreamingChatModel.builder().modelName("deepseek-r1:1.5b").build();
  //
  //    return Flux.create(
  //        sink -> {
  //          chatModel.chat(
  //              messages,
  //              new StreamingChatResponseHandler() {
  //                @Override
  //                public void onPartialResponse(String partialResponse) {
  //                  sink.next(partialResponse);
  //                  // data:需要帮助，欢迎
  //                  //
  //                  // data:随时向我提问！
  //                }
  //
  //                @Override
  //                public void onCompleteResponse(ChatResponse completeResponse) {
  //                  //                    log.info("complete:{}", completeResponse);
  //                  sink.next("[DONE]");
  //                  sink.complete();
  //                }
  //
  //                @Override
  //                public void onError(Throwable error) {
  //                  sink.error(error);
  //                }
  //              });
  //        });
  //  }
  //
  //  /**
  //   * 请求
  //   *
  //   * @param userId userId
  //   * @param message message
  //   */
  //  public record StreamChatRequest(String userId, String message) {}
}
